School of Surveying and Spatial Information Systems
The University of New South Wales
Extraction of Building
Outlines using LIDAR Imagery
Supervised by Dr S. Lim
Various methods have been developed to measure the physical presence of objects with high positional accuracy. One of the most recent methods is the development of Airborne Laser Scanning, a method that scans the landscape through multiple passes, measuring the return time from pulses of laser light aboard the aircraft. The bi-product of the laser scan is a very accurate, dense cloud of points in 3D space that mirrors the landscape. The dilemma however is that in spite of the ability to measure very accurately the landscape in short period of time, the automatic detection and interpretation of the points remains difficult. Therefore the point clouds need to be modelled, so as to allow for the making of accurate 3 D maps.
Thus the aim of this thesis is to extract 3D GIS polygons of the tall buildings from raw LIDAR data, and produce a 3D UNSW campus model. A process achieved by Semi-Automatic Feature Extraction using the tools available within the ArcGIS suite.
LIDAR is an acronym for Light Detection and Ranging, LIDAR technology uses Airborne Global Positioning with an Inertial Measurement Unit to determine the position and orientation of the system. The LIDAR unit uses a dispersed laser light pulsing at 25 kilohertz to make direct measurements from the aircraft to the earth's surface. The unit then measures distances to the first and last return from each pulse of light. The raw data represents a three-dimensional ‘First Surface Model’ and a ‘Bare-earth Model.’(AAM Geoscan. 2001) The bare-earth Model can be used to generate contours that represent the shape and elevation of the ground on accurate maps, and the combination of the two models can be used to estimate heights of features on the earth's surface. In this instance the buildings located on UNSW campus. The loaded data in last return DEM can be seen below in Qt modeler.
Automated packages exist to extract building outlines however they are not readily available or reliable, as the algorithm is designed specifically for the data set. However tools available in ArcGIS can semi automate the process.
By having the data in raster format the extraction can be done.
The photo below shows the extracted building outlines overlayed the last return UNSW campus model
To achieve this steps used include:
Disconnected Editing-> extract
This allows the data the user has selected to be separated from the main DEM
Spatial analyst -> Raster calculator
This allows the user to define the points of LIDAR data of which they want Example include using the Height greater than 45m but less tha 50m.
ArcToolbox -> Conversion Tools -> From Raster -> Raster to Polygon
This converts to polygon so the buildings can be edited
ArcToolbox -> Data management tools -> Features -> Features to Line
Here the user can get the general outline of the points selected
ArcToolbox -> Data management tools -> Generalization-> Simplified Line
The Line can now be simplified to fit the general shape of the building
ArcToolbox -> Data management tools -> Features -> Features to Polygon
The line now edited can be reclassified as a polygon so heights can be assigned to it to create a 3d model
Once the building outlines are extracted the building heights are assigned. Using the classify tool statistics can be obtained from the building height
Naturally all buildings do not have flat roofs. Thus the slope of the outline is analysed also
the spatial analyst tool can be used to determine the slope.
Having the building outlines determined plus now the height and shape of the building all this information can be used to create a 3D model in ArcScene.
These buildings can the be overlayed a triangulated irregular network or TIN which is a 3D representation of contours of the UNSW campus
The final outcome
The results were attempted to be of the highest possible accuracy the data would allow. In some of the cases, in particular the buildings, which were orthodox in shape, stood well above its surrounds or had limited noise, like vegetation surrounding their outline were extracted quite precisely. Examples of this include the Clancy auditorium as well as the UNSW Library.
However as with the major problem with the progression of LIDAR building extraction, overhanging vegetation, unorthodox building shape and clusters of buildings within close proximity, the results became worse, or couldn’t be extracted to accurate shapes
In these situations, automatic packages use buildings height and shapes are based on assumptions. This allows for the accuracy to be maintained too as high as possible, but cannot be guaranteed. The other significant difference is that the actual use of the LIDAR points does not occur. However depending on the scope of the work, these assumptions can be very appropriate. This is particularly true when there is a need for an estimation, approximation or rough guide. (Sithole G. 2005)
Advantages to Automation include:
: The user will be able develop processes specifically tailored to your data,
and have the ability to make changes to processing procedures as needed to meet
the challenges of your particular situation. The user will also have the ability
to take processes you have developed and use them as modules of larger and more
complex processes. Another aspect of control is the ability to apply the same
settings to processes repeatedly without the possibility of typographic or other
human error introducing inconsistencies between datasets.
: The user will be able develop processes specifically tailored to your data, and have the ability to make changes to processing procedures as needed to meet the challenges of your particular situation. The user will also have the ability to take processes you have developed and use them as modules of larger and more complex processes. Another aspect of control is the ability to apply the same settings to processes repeatedly without the possibility of typographic or other human error introducing inconsistencies between datasets.(Hewett M 2004)
G. (2005). Segmentation and Classification of Airborne Laser Scanner Data,
Delft, The Netherlands
M. (2004). Automating Feature Extraction with the ArcGIS Spatial. Analyst
Extension. Document available online at
Author unknown. (2004). Automated
building extraction and reconstruction using LIDAR data. Document available
Finlayson C. (2004). A
complete Building extraction system from elevation data. Document available
AAM GeoScan (2001). Scanning the Horizons, (17 Sep. 2001). Document available from AAMHatch on request
For more information, please contact:
Dr S. LIm
School of Surveying and Spatial Information Systems
University of New South Wales
UNSW SYDNEY NSW 2052